The present invention relates to treatment planning for arterial stenosis, and more particularly, to selecting which stenoses or lesions to stent based on medical image data of a patient.
Cardiovascular disease (CVD) is the leading cause of deaths worldwide. Among various CVDs, coronary artery disease (CAD) accounts for nearly fifty percent of those deaths. Local narrowing of a blood vessels, or stenosis, represents an important cause of cardiovascular diseases. Such stenoses typically develop gradually over time, and can develop in different parts of the arterial circulation, such as the coronary arteries, renal arteries, peripheral arteries, carotid artery, cerebral artery, etc. Such a local narrowing can also be the result of a congenital defect. One therapy widely used for treating arterial stenosis is stenting, i.e., the placement of a metal or polymer stent in the artery to open up the lumen, and hence facilitate the flow of blood. When dealing with coronary artery stenosis, the stenting therapy is referred to as percutaneous coronary intervention (PCI).
In recent years, there has been considerable focus on computational approaches for modeling the flow of blood in the human cardiovascular system. When used in conjunction with patient-specific anatomical models extracted from medical images, such computational techniques can provide important insights into the structure and function of the cardiovascular system.